Source apportionment and risk assessment of trace element pollution in Yamuna river water in Delhi: a probability based approach

Aithani, Deeksha; Jyethi, Darpa Saurav; Yadav, Amit K.; Siddiqui, Zainab; Khillare, P. S.

doi:10.1080/1573062x.2022.2086885

Cited by 4 publications

(2 citation statements)

References 38 publications

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“…Several trace elements were detected in our research and several stations have relatively high levels of trace element, such as Cu (≥0.0014 mg/L), Pb (≥0.0005 mg/L), Cd (≥0.0001 mg/L), Zn (≥0.01 mg/L), As (≥0.0016 mg/L), Ni (≥0.001 mg/L), T-Cr (≥0.001 mg/L) ( Figure 2 ). Trace elements like Fe, Cu, Zn, Ni and others are important for the proper functioning of biological systems and their deficiency or excess are detrimental for aquatic microorganisms ( Aithani et al, 2023 ). Trace element in water is thought to be difficult to degrade, bioaccumulative and ecologically toxic ( Wu et al, 2016 ; Saha and Paul, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Du,

Ren,

Zhong

et al. 2024

Front. Microbiol.

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In the context of human activities and climate change, the gradual degradation of coastal water quality seriously threatens the balance of coastal and marine ecosystems. However, the spatiotemporal patterns of coastal water quality and its driving factors were still not well understood. Based on 31 water quality parameters from 2015 to 2020, a new approach of optimizing water quality index (WQI) model was proposed to quantitatively assess the spatial and temporal water quality along tropical Hainan Island, China. In addition, pollution sources were further identified by factor analysis and the effects of pollution source on water quality was finally quantitatively in our study. The results showed that the average water quality was moderate. Water quality at 86.36% of the monitoring stations was good while 13.53% of the monitoring stations has bad or very bad water quality. Besides, the coastal water quality had spatial and seasonal variation, along Hainan Island, China. The water quality at “bad” level was mainly appeared in the coastal waters along large cities (Haikou and Sanya) and some aquaculture regions. Seasonally, the average water quality in March, October and November was worse than in other months. Factor analysis revealed that water quality in this region was mostly affected by urbanization, planting and breeding factor, industrial factor, and they played the different role in different coastal zones. Waters at 10.23% of monitoring stations were at the greatest risk of deterioration due to severe pressure from environmental factors. Our study has significant important references for improving water quality and managing coastal water environment.

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Section: Discussionmentioning

confidence: 99%

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Du,

Ren,

Zhong

et al. 2024

Front. Microbiol.

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“…As cities grow and more chemical factories move away, so do the number of contaminated sites and the types of contaminants. A contaminated site is one of the current study hotspots, such as the distribution characteristics [ 1 , 2 , 3 ], risk assessment [ 4 , 5 ], remediation [ 6 , 7 , 8 , 9 , 10 ], and impact on human health [ 11 , 12 ]. Due to the typical characteristics of hidden, irreversible, and complex contaminated sites in China [ 13 ], a contaminated sites investigation has received more attention.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Chain-Type Direct Push Drilling Rig for Contaminated Sites

Sun

Zhou

Cao

et al. 2023

IJERPH

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For sites where volatile organic compounds are present, the direct push method, in combination with other sensors for investigation, is a powerful method. The investigation process is an integrated drilling and sensing process, but the trajectory of the probe carrying the sensor is ambiguous. This paper explores and introduces the application of a chain-type direct push drilling rig by designing and building a chain-type direct push miniature drilling rig. This rig allows for indoor experimental studies of direct push trajectories. The chain-type direct push drilling model is proposed based on the mechanism of chain transmission. The drilling rig provides a steady direct thrust through the chain, which is driven by a hydraulic motor. In addition, the drilling tests and results described prove that the chain could be applied to direct push drilling. The chain-type direct push drilling rig can drill to a depth of 1940 mm in single-pass and up to 20,000 mm in multiple passes. The test results also indicate that it drills a total length of 462.461 mm and stops after 87.545 s of operation. The machine can provide a drilling angle of 0–90° and keep the borehole angle fluctuating within 0.6° with the characteristics of strong adjustability, flexibility, continuity, stability, and low disturbance, which is of great value and significance for studying the drilling trajectory of direct push tools and obtaining more accurate investigation data.

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Spatiotemporal variations, sources, pollution status and health risk assessment of dissolved trace elements in a major Arabian Sea draining river: insights from multivariate statistical and machine learning approaches

Singh,

Das,

Sharma

et al. 2024

Environ Geochem Health

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Source apportionment and risk assessment of trace element pollution in Yamuna river water in Delhi: a probability based approach

Cited by 4 publications

References 38 publications

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Design and Implementation of a Chain-Type Direct Push Drilling Rig for Contaminated Sites

Spatiotemporal variations, sources, pollution status and health risk assessment of dissolved trace elements in a major Arabian Sea draining river: insights from multivariate statistical and machine learning approaches

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